Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics

Informationen zum Autor YI PAN, PHD, is the Chair and Full Professor in the Department of Computer Science at Georgia State University, and a Visiting Chair Professor in the School of Information Science and Engineering at Central South University in Changsha, China. MIN LI, PHD, is Associate Professor in the School of Information Science and Engineering and a postdoctoral associate in the State Key Laboratory of Medical Genetics at Central South University in Changsha, China. JIANXIN WANG, PHD, is Associate Dean and Full Professor in the School of Information Science and Engineering at Central South University in Changsha, China. Klappentext An in-depth look at the latest research, methods, and applications in the field of protein bioinformaticsThis book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems.Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization* Includes many tables and illustrations demonstrating concepts and performance figuresAlgorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics. Zusammenfassung An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. Inhaltsverzeichnis PREFACE ixCONTRIBUTORS xvI FROM PROTEIN SEQUENCE TO STRUCTURE1 EMPHASIZING THE ROLE OF PROTEINS IN CONSTRUCTION OF THE DEVELOPMENTAL GENETIC TOOLKIT IN PLANTS 3Anamika Basu and Anasua Sarkar2 PROTEIN SEQUENCE MOTIF INFORMATION DISCOVERY 41Bernard Chen3 IDENTIFYING CALCIUM BINDING SITES IN PROTEINS 57Hui Liu and Hai Deng4 REVIEW OF IMBALANCED DATA LEARNING FOR PROTEIN METHYLATION PREDICTION 71Zejin Ding and Yan-Qing Zhang5 ANALYSIS AND PREDICTION OF PROTEIN POSTTRANSLATIONAL MODIFICATION SITES 91Jianjiong Gao, Qiuming Yao, Curtis Harrison Bollinger, and Dong XuII PROTEIN ANALYSIS AND PREDICTION6 PROTEIN LOCAL STRUCTURE PREDICTION 109Wei Zhong, Jieyue He, Robert W. Harrison, Phang C. Tai, and Yi Pan7 PROTEIN STRUCTURAL BOUNDARY PREDICTION 125Gulsah Altun8 PREDICTION OF RNA BINDING SITES IN PROTEINS 153Zhi-Ping Liu and Luonan Chen9 ALGORITHMIC FRAMEWORKS FOR PROTEIN DISULFIDE CONNECTIVITY DETERMINATION 171Rahul Singh, William Murad, and Timothy Lee10 PROTEIN CONTACT ORDER PREDICTION: UPDATE 205Yi Shi, Jianjun Zhou, David S. Wishart, and Guohui Lin11 PROGRESS IN PREDICTION OF OXIDATION STATES OF CYSTEINES VIA COMPUTATIONAL APPROAC...

Autorentext

YI PAN, PHD, is the Chair and Full Professor in the Department of Computer Science at Georgia State University, and a Visiting Chair Professor in the School of Information Science and Engineering at Central South University in Changsha, China. MIN LI, PHD, is Associate Professor in the School of Information Science and Engineering and a postdoctoral associate in the State Key Laboratory of Medical Genetics at Central South University in Changsha, China. JIANXIN WANG, PHD, is Associate Dean and Full Professor in the School of Information Science and Engineering at Central South University in Changsha, China.

Klappentext

An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization * Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.

Inhalt

PREFACE ix CONTRIBUTORS xv I FROM PROTEIN SEQUENCE TO STRUCTURE 1 EMPHASIZING THE ROLE OF PROTEINS IN CONSTRUCTION OF THE DEVELOPMENTAL GENETIC TOOLKIT IN PLANTS 3 Anamika Basu and Anasua Sarkar 2 PROTEIN SEQUENCE MOTIF INFORMATION DISCOVERY 41 Bernard Chen 3 IDENTIFYING CALCIUM BINDING SITES IN PROTEINS 57 Hui Liu and Hai Deng 4 REVIEW OF IMBALANCED DATA LEARNING FOR PROTEIN METHYLATION PREDICTION 71 Zejin Ding and Yan-Qing Zhang 5 ANALYSIS AND PREDICTION OF PROTEIN POSTTRANSLATIONAL MODIFICATION SITES 91 Jianjiong Gao, Qiuming Yao, Curtis Harrison Bollinger, and Dong Xu II PROTEIN ANALYSIS AND PREDICTION 6 PROTEIN LOCAL STRUCTURE PREDICTION 109 Wei Zhong, Jieyue He, Robert W. Harrison, Phang C. Tai, and Yi Pan 7 PROTEIN STRUCTURAL BOUNDARY PREDICTION 125 Gulsah Altun 8 PREDICTION OF RNA BINDING SITES IN PROTEINS 153 Zhi-Ping Liu and Luonan Chen 9 ALGORITHMIC FRAMEWORKS FOR PROTEIN DISULFIDE CONNECTIVITY DETERMINATION 171 Rahul Singh, William Murad, and Timothy Lee 10 PROTEIN CONTACT ORDER PREDICTION: UPDATE 205 Yi Shi, Jianjun Zhou, David S. Wishart, and Guohui Lin 11 PROGRESS IN PREDICTION OF OXIDATION STATES OF CYSTEINES VIA COMPUTATIONAL APPROACHES 217 Aiguo Du, Hui Liu, Hai Deng, and Yi Pan 12 COMPUTATIONAL METHODS IN CRYOELECTRON MICROSCOPY 3D STRUCTURE RECONSTRUCTION 231 Fa Zhang, Xiaohua Wan, and Zhiyong Liu III PROTEIN STRUCTURE ALIGNMENT AND ASSESSMENT 13 FUNDAMENTALS OF PROTEIN STRUCTURE ALIGNMENT 255 Mark Brandt, Allen Holder, and Yosi Shibberu 14 DISCOVERING 3D PROTEIN STRUCTURES FOR OPTIMAL STRUCTURE ALIGNMENT 281 Tomás Novosád, Václav Snásel, Ajith Abraham, and Jack Y. Yang 15 ALGORITHMIC METHODOLOGIES FOR DISCOVERY OF NONSEQUENTIAL PRO…